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Tuesday, January 20, 2015

Announcing the launch of Dr. Jerome Carter's Clinical Workflow Center

I have for some time closely followed the postings of Jerome Carter, MD at his blog EHR Science. Now comes his new initiative (I've known about it since last week, and have registered there, but he asked me to keep quiet about it until he went "live"). I know we're all now in the thrall of sexy cutting-edge healthcare space digitech, but it behooves us to not lose sight of some critical fundamentals. HIT devices and software apps are just tools. They still have to be effectively embedded in the workflows. Yeah, "disruption" is now a way cool term among the digerati and econ theorists, but actual disruption of clinical workflows makes those in the trenches crazy --  and risks harming or killing patients.

Clinical Workflow Center is a site dedicated to everything clinical workflow. It was created with the following goals in mind: 1) teaching clinical workflow analysis methods and 2) demonstrating the mathematical properties of clinical workflows and how those properties can be used to solve real-world problems. Since I consider workflow analysis to be a fundamental informatics skill, there are tutorials covering important workflow concepts and analysis techniques.  A Q&A forum is provided to for those who wish to share and ask questions. Resource pages offer a link to a wide varierty of useful materials.  Clinical Workflow Center is a companion site to EHR Science.

Why create a site decidated to clinical workflow topics?
Workflow disruptions are increasingly being recognized as workarounds, usability issues, safety concerns, and CDS problems. The first step to solving any problem is recognizing that it exists. In the case of HIT, this means acknowledging that clinical care consists of a series of specialized workflows. Clinical care consists of directed sequences of tasks that use, generate, or share information and that involve one or more individuals or machines. If the task sequence is wrong, the information incorrect or unavailable, or the wrong people, software or equipment involved, problems occur.

EHR system-clinical work impedance The automation of clinical care with current EHR systems has resulted in numerous complaints from clinical professionals who are fed up and discouraged by systems that make their jobs harder to do. The number of workflow disruptions that occur as a result of EHR use should surprise no one. Disruptions were to be expected because EHR systems are archival systems that do not contain models of clinical work. Making matters worse is the fact that EHR systems have their own internal workflows. Consequently, a good portion of EHR training is spent helping EHR users learn to adapt their workflows to those of the software. Thus, training times are one hint of impending EHR system-clinical work impedance and attendant clinician misery.

The problem with current clinical workflow approaches Beyond training, entire organizations have to adapt their processes to match the hard-coded workflows of EHR systems. Recent demands for improved system usability indicate the amount of misery that EHR-clinical work impedance has caused. However, the solutions proposed do not seem to grasp just how fundamentally important workflow issues are.

Understanding exactly how clinical work is disrupted or enhanced, whether using software or not, requires the ability to precisely model clinical work.   And here is where the first major problem arises. Most modeling approaches used in clinical settings are based on flowcharts and swim-lane diagrams. Neither of these tools offers a means to capture all information movements, resource interactions and complex task sequences in one unified model. Unfortunately, attempts to improve the fidelity of workflow models often involve adding UML (e.g. state, activity) and other diagrams to the mix such as data flow diagrams. The key to better modeling is not more diagrams, but rather a single framework that allows for representation of all workflow concepts.

Obviously, detail is required to determine how the information needs of a nurse doing a patient intake are best mapped to his/her physical actions. This leads to the second problem: current workflow modeling efforts are usually insufficiently detailed for the processes they represent. This lack of detail is evident in workflow modeling training materials (see Clinical Workflow Analysis: The Value of Task-Level Detail ).

Workflow modelers seeking to add detail to their diagrams have another problem: there are no formal standards for encoding clinical work such as task names, step increments, information requirements, or notation symbols. Lacking such standards, models of the same workflows from different modelers will likely differ significantly. Such variation impedes learning and the progress of clinical informatics as it concerns understanding the interplay of clinical work and clinical care software (see Modeling Clinical Workflows and Processes). Fortunately, there has been a significant amount of workflow research in the last 20 years, and all of it can be applied to health care.

Workflow research outside of clinical care Automation of business processes has been a major focus of workflow research in the computer science, engineering and business communities. While automating processes is a worthwhile goal, workflow research — especially that focused on creating process models — can also be used to study clinical care activities at the lowest levels and build abstract models for analysis. Automating a process before fully understanding it can be disastrous. If one is losing money because of bad billing processes, automating those processes “as is” will result in bigger losses. Thus, some degree of analysis and modeling are essential before any attempts at automation. Clinical organizations that have been successful in implementing clinical software get this point.

Workflow patterns have the ability to express every major aspect of clinical workflows. Yes, they must be adapted to clinical use, but the basic concepts stand. Even better, workflow patterns and Petri nets are based in mathematics, which assures that precise meanings and notations are possible. Again, some changes and adjustments are required for clinical care, but the required changes are not rocket science. Aside from workflow patterns and Petri nets, I will go out on a limb (not far) and state that every clinical workflow (e.g., task sequence, information movements, and resource interactions) can be represented by a combination of common mathematical objects–logic, sets, functions/relations, and graphs. It is time to take the rich legacy of workflow research from computer science, engineering and business and apply it to understanding how clinical care happens.

Workflow disruptions by any other name…When caring for a patient, information is important. When and/or where in a care process information is required, collected, saved or shared are not simply usability issues, or safety problems, or human factors concerns, they are basic workflow issues as well. Addressing information needs requires close attention to workflow tasks and how they are sequenced. Who or what will participate in or complete a task are likewise workflow issues.

Given the importance of workflow to clinical care, the ability to expertly conduct workflow analyses should be right up there with being able to normalize a database or understand basic programming concepts as a training curriculum objective. In light of the fact that so many aspects of software selection/implementation, safety, usability, and CDS are workflow-based, clinical informaticists should be experts in analyzing and modeling clinical processes.
I hope this effort gets significant traction. Clinical workflows are irreducibly complex, high cognitive burden processes, and, given that digital health IT is not going away, the topic needs more effective and more widely visible analytical scrutiny and collaboration in pursuit of material improvement.

to wit

We’re all dressed up with nowhere to go. We’ve got our labs, real-time wireless sensor data, genomic sequence information, and images. Our ability to generate big medical data about an individual has far outstripped any semblance of managing it, and we can’t even build the full GIS yet. There is not a single electronic medical record (EMR ) system today that is set up to bring all this data together in a meaningful way— not just to aggregate it, but to provide the full analysis of all one’s medical information. It’s like we invented the printing press but haven’t figured out the card catalog. This isn’t necessarily because no one has tried; there are plenty of obstacles, but also, in spite of them, some early signs of progress. We’re talking about access, not ownership, a baby step in the right direction... [pg 125]
Doctors and the Medical Community 
With disinclination to change embedded in the medical community, reflected by the average time gap of seventeen years from innovation to adoption in medical practice, we need a cultural change. While digital native doctors just coming out of medical school or finishing residency training understand the sea change that is unfolding, there are millions of practicing physicians around the world who do not. We don’t have time to wait for a new generation of doctors and health care professionals to take hold. Cultural change is exceedingly difficult, but given the other forces in the iMedicine galaxy, especially the health care economic crisis that has engendered desperation, it may be possible to accomplish. An aggressive commitment to the education and training of practicing physicians to foster their use of the new tools would not only empower their patients, but also themselves. Eliminating the enormous burden of electronic charting or use of scribes by an all-out effort for natural language processing of voice during a visit would indeed be liberating... [pg 289]

Topol, Eric (2015-01-06). The Patient Will See You Now: The Future of Medicine is in Your Hands Basic Books. Kindle Edition.
Fabulous book.

Dr. Carter certainly has the Cred in this area.
Jerome H. Carter, MD, FACP, FHIMSS  is a board-certified internist who has been active in the field of medical informatics since completing a fellowship in 1987. He is also Adjunct Clinical Associate Professor of Medical Education at Morehouse School of Medicine (MSM) in Atlanta, GA.

Dr. Carter was previously Assistant Professor of Medicine at the University of Alabama-Birmingham (UAB) where he was Director of Informatics for the 1917  Patient Care and Research Clinic. At the 1917 Clinic, he led a five-year effort to design, build, and implement an electronic health record system optimized for patient care and outcomes research. During that time, he also directed the selection and implementation of a dental practice management and electronic record system.

While at UAB, Dr. Carter was also a member of the graduate faculty in the Master of Health Informatics Program. For six years, he was course director of “Clinical Documentation and Information Systems in Support of Patient Care”, which addressed issues related to the implementation and use of clinical information systems. A major emphasis of the course was the analysis of information system implementations in a variety of settings. Over the period 1995 to  2001, more than 40 health care entities from small practices to hospitals were studied in an effort to understand what makes for successful implementations.

Dr. Carter is the editor of Electronic Health Records, Second Edition (April 2008), published by the American College of Physicians. He served as a member of the American College of Physicians' Subcommittee on Medical Informatics from 1993-2001 (Chair, 1997-2001). From 2003 through 2007, he served on the Board of Scientific Counselors, Lister Hill Center, of the National Library of Medicine. Dr. Carter was co-chair of the HIMSS Electronic Health Records Adoption Task Force from  2007  until 2009.

Dr. Carter is a member of the following organizations: American College of Physicians, Association for Computing Machinery, American Medical Informatics Association, Healthcare Information and Management Systems Society,  IEEE - Computer Society, and CompTIA.
From EHR Science
One thing that seems important to address from the outset is the definition of clinical workflow. There are many definitions of workflow concepts available. I favor those provided by way of workflow patterns. Here are the definitions provided by Russell, et al. (1).

A workflow or workflow model is a description of a business process in sufficient detail that it is able to be directly executed by a workflow management system. A workflow model is composed of a number of tasks which are connected in the form of a directed graph.
These definitions are focused on automation and not clinical work. I would like to adapt these definitions, and workflow patterns in general, for clinical work. Should these efforts be successful, the result would be a set of shared conventions (e.g., definitions, analysis methods, terminology, modeling representations) for clinical workflow analyses and models that are easily shared and understood across clinical sites and application domains—usability, CDS, patient safety, software design. And, in keeping with the definitions provided by Russell et al., these models would also be executable by workflow technology. Flowcharts and swim lanes are great for discussions, but they are not executable.
Here are the definitions that will be used on CWC.

  • Clinical Work – Activities performed to assess, change or maintain the health of a patient.
  • Clinical Process – A specific clinical work activity undertaken by one or more clinical professionals with a specific start point, end point, and an expected outcome.
  • Clinical Workflow – The directed series of steps comprising a clinical process that 1) are performed by people/equipment/computers and 2) consume, transform and/or produce information. (Note that patient outcomes count as information.)
  • Clinical Workflow Model – A human-readable visual representation of a clinical workflow that can be executed by workflow technology.
One of my old REC "directed graphs." Fairly high level, marginally adequate. Conducted a pre-EHR implementation clipboard/walk-thru interview of the doc and his staff. Tried to compactly show what would go away and what would change via the conversion from paper to electronic.

The problem with these is that they are simply "logic flows" (laid out to fit pagination constraints to boot) and do not depict the time consumed, or the hand-offs, explicitly (my crude proxy for the hand-offs was color-coding).

Hand-offs ("swimlanes") and time consumption might look like this:

Click to enlarge

See my prior post Clinical workflow: "YAWL," y'all? for more of my brief workflow concept illustrations.


From the President's 2015 SOTU transcript: 
"21st century businesses will rely on American science, technology, research and development. I want the country that eliminated polio and mapped the human genome to lead a new era of medicine — one that delivers the right treatment at the right time. In some patients with cystic fibrosis, this approach has reversed a disease once thought unstoppable. Tonight, I’m launching a new Precision Medicine Initiative to bring us closer to curing diseases like cancer and diabetes — and to give all of us access to the personalized information we need to keep ourselves and our families healthier.

I intend to protect a free and open internet, extend its reach to every classroom, and every community, and help folks build the fastest networks, so that the next generation of digital innovators and entrepreneurs have the platform to keep reshaping our world."
As noted on, 
POTUS Just Announced a New Precision Medicine Initiative
Precision medicine is an emerging approach to treating illnesses that takes into account a patient’s individual genetic make-up as well as molecular subtypes of diseases to improve the chances of successful treatment.
We'll have to see what comprises the details.

More to come...

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